2: #include <../src/mat/impls/aij/mpi/mpiaij.h>
5: /*@C
6: MatCreateMPIAIJPERM - Creates a sparse parallel matrix whose local
7: portions are stored as SEQAIJPERM matrices (a matrix class that inherits
8: from SEQAIJ but includes some optimizations to allow more effective
9: vectorization). The same guidelines that apply to MPIAIJ matrices for
10: preallocating the matrix storage apply here as well.
12: Collective on MPI_Comm 14: Input Parameters:
15: + comm - MPI communicator
16: . m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
17: This value should be the same as the local size used in creating the
18: y vector for the matrix-vector product y = Ax.
19: . n - This value should be the same as the local size used in creating the
20: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
21: calculated if N is given) For square matrices n is almost always m.
22: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
23: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
24: . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix
25: (same value is used for all local rows)
26: . d_nnz - array containing the number of nonzeros in the various rows of the
27: DIAGONAL portion of the local submatrix (possibly different for each row)
28: or PETSC_NULL, if d_nz is used to specify the nonzero structure.
29: The size of this array is equal to the number of local rows, i.e 'm'.
30: For matrices you plan to factor you must leave room for the diagonal entry and
31: put in the entry even if it is zero.
32: . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local
33: submatrix (same value is used for all local rows).
34: - o_nnz - array containing the number of nonzeros in the various rows of the
35: OFF-DIAGONAL portion of the local submatrix (possibly different for
36: each row) or PETSC_NULL, if o_nz is used to specify the nonzero
37: structure. The size of this array is equal to the number
38: of local rows, i.e 'm'.
40: Output Parameter:
41: . A - the matrix
43: Notes:
44: If the *_nnz parameter is given then the *_nz parameter is ignored
46: m,n,M,N parameters specify the size of the matrix, and its partitioning across
47: processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
48: storage requirements for this matrix.
50: If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one
51: processor than it must be used on all processors that share the object for
52: that argument.
54: The user MUST specify either the local or global matrix dimensions
55: (possibly both).
57: The parallel matrix is partitioned such that the first m0 rows belong to
58: process 0, the next m1 rows belong to process 1, the next m2 rows belong
59: to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.
61: The DIAGONAL portion of the local submatrix of a processor can be defined
62: as the submatrix which is obtained by extraction the part corresponding
63: to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the
64: first row that belongs to the processor, and r2 is the last row belonging
65: to the this processor. This is a square mxm matrix. The remaining portion
66: of the local submatrix (mxN) constitute the OFF-DIAGONAL portion.
68: If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.
70: When calling this routine with a single process communicator, a matrix of
71: type SEQAIJPERM is returned. If a matrix of type MPIAIJPERM is desired
72: for this type of communicator, use the construction mechanism:
73: MatCreate(...,&A); MatSetType(A,MPIAIJ); MatMPIAIJSetPreallocation(A,...);
75: By default, this format uses inodes (identical nodes) when possible.
76: We search for consecutive rows with the same nonzero structure, thereby
77: reusing matrix information to achieve increased efficiency.
79: Options Database Keys:
80: + -mat_no_inode - Do not use inodes
81: . -mat_inode_limit <limit> - Sets inode limit (max limit=5)
82: - -mat_aij_oneindex - Internally use indexing starting at 1
83: rather than 0. Note that when calling MatSetValues(),
84: the user still MUST index entries starting at 0!
86: Level: intermediate
88: .keywords: matrix, cray, sparse, parallel
90: .seealso: MatCreate(), MatCreateSeqAIJPERM(), MatSetValues()
91: @*/
92: PetscErrorCodeMatCreateMPIAIJPERM(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A) 93: {
95: PetscMPIInt size;
98: MatCreate(comm,A);
99: MatSetSizes(*A,m,n,M,N);
100: MPI_Comm_size(comm,&size);
101: if (size > 1) {
102: MatSetType(*A,MATMPIAIJPERM);
103: MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);
104: } else {
105: MatSetType(*A,MATSEQAIJPERM);
106: MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);
107: }
108: return(0);
109: }
111: EXTERN_C_BEGIN112: extern PetscErrorCode MatConvert_SeqAIJ_SeqAIJPERM(Mat,const MatType,MatReuse,Mat*);
113: extern PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]);
114: EXTERN_C_END
116: EXTERN_C_BEGIN
119: PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJPERM(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])120: {
121: Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data;
125: MatMPIAIJSetPreallocation_MPIAIJ(B,d_nz,d_nnz,o_nz,o_nnz);
126: MatConvert_SeqAIJ_SeqAIJPERM(b->A, MATSEQAIJPERM, MAT_REUSE_MATRIX, &b->A);
127: MatConvert_SeqAIJ_SeqAIJPERM(b->B, MATSEQAIJPERM, MAT_REUSE_MATRIX, &b->B);
128: return(0);
129: }
130: EXTERN_C_END
132: EXTERN_C_BEGIN
135: PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat A,const MatType type,MatReuse reuse,Mat *newmat)136: {
138: Mat B = *newmat;
141: if (reuse == MAT_INITIAL_MATRIX) {
142: MatDuplicate(A,MAT_COPY_VALUES,&B);
143: }
145: PetscObjectChangeTypeName( (PetscObject) B, MATMPIAIJPERM);
146: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocation_C",
147: "MatMPIAIJSetPreallocation_MPIAIJPERM",
148: MatMPIAIJSetPreallocation_MPIAIJPERM);
149: *newmat = B;
150: return(0);
151: }
152: EXTERN_C_END
155: EXTERN_C_BEGIN
158: PetscErrorCode MatCreate_MPIAIJPERM(Mat A)159: {
163: MatSetType(A,MATMPIAIJ);
164: MatConvert_MPIAIJ_MPIAIJPERM(A,MATMPIAIJPERM,MAT_REUSE_MATRIX,&A);
165: return(0);
166: }
167: EXTERN_C_END
169: /*MC
170: MATAIJPERM - MATAIJPERM = "AIJPERM" - A matrix type to be used for sparse matrices.
172: This matrix type is identical to MATSEQAIJPERM when constructed with a single process communicator,
173: and MATMPIAIJPERM otherwise. As a result, for single process communicators,
174: MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported
175: for communicators controlling multiple processes. It is recommended that you call both of
176: the above preallocation routines for simplicity.
178: Options Database Keys:
179: . -mat_type aijperm - sets the matrix type to "AIJPERM" during a call to MatSetFromOptions()
181: Level: beginner
183: .seealso: MatCreateMPIAIJPERM(), MATSEQAIJPERM, MATMPIAIJPERM
184: M*/